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  • Title: Database Extraction of Metabolite Information of Drug Candidates: Analysis of 27 AstraZeneca Compounds with Human Absorption, Distribution, Metabolism, and Excretion Data.
    Author: Iegre J, Hayes MA, Thompson RA, Weidolf L, Isin EM.
    Journal: Drug Metab Dispos; 2016 May; 44(5):732-40. PubMed ID: 26868617.
    Abstract:
    As part of the drug discovery and development process, it is important to understand the human metabolism of a candidate drug prior to clinical studies. Preclinical in vitro and in vivo experiments across species are conducted to build knowledge concerning human circulating metabolites in preparation for clinical studies; therefore, the quality of these experiments is critical. Within AstraZeneca, all metabolite identification (Met-ID) information is stored in a global database using ACDLabs software. In this study, the Met-ID information derived from in vitro and in vivo studies for 27 AstraZeneca drug candidates that underwent human absorption, distribution, metabolism, and excretion studies was extracted from the database. The retrospective analysis showed that 81% of human circulating metabolites were previously observed in preclinical in vitro and/or in vivo experiments. A detailed analysis was carried out to understand which human circulating metabolites were not captured in the preclinical experiments. Metabolites observed in human hepatocytes and rat plasma but not seen in circulation in humans (extraneous metabolites) were also investigated. The majority of human specific circulating metabolites derive from multistep biotransformation reactions that may not be observed in in vitro studies within the limited time frame in which cryopreserved hepatocytes are active. Factors leading to the formation of extraneous metabolites in preclinical studies seemed to be related to species differences with respect to transporter activity, secondary metabolism, and enzyme kinetics. This retrospective analysis assesses the predictive value of Met-ID experiments and improves our ability to discriminate between metabolites expected to circulate in humans and irrelevant metabolites seen in preclinical studies.
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